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Abstract

The Global Positioning System (GPS) has been widely used in navigation, surveying, geophysical and geodynamic studies, machine guidance, etc. High-precision GPS applications such as geodetic surveying need millimeter and centimeter level accuracy. Since GPS signals are affected by atmospheric effects, methods of correcting or eliminating ionospheric and tropospheric bias are needed in GPS data processing. Relative positioning can be used to mitigate the atmospheric effect, but its efficiency depends on the baseline lengths. Air pollution is a serious problem globally, especially in developing countries that causes health problems to humans and damage to the ecosystem. Respirable suspended particles are coarse particles with a diameter of 10 micrometers or less, also known as PM10. Moreover, fine particles with a diameter of 2.5 micrometers or less are known as PM2.5. GPS signals travel through the atmosphere before arriving at receivers on the Earth’s surface, and the research question posed in this paper is: are GPS signals affected by the increased concentration of the PM2.5/PM10 particles? There is no standard model of the effect of PM2.5/PM10 particles on GPS signals in GPS data processing, although an approximate generic model of non-gaseous atmospheric constituents (<1 mm) can be found in the literature. This paper investigates the effect of the concentration of PM2.5/PM10 particles on GPS signals and validates the aforementioned approximate model with a carrier-to-noise ratio (CNR)-based empirical method. Both the approximate model and the empirical results show that the atmospheric PM2.5/PM10 particles and their concentrations have a negligible effect on GPS signals and the effect is comparable with the noise level of GPS measurements.
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).